distratto: Impaired Driving Detection Using Textile Sensors

摘要

Statistical data show that the driving-related accidents and human casualties caused by vehicles are on the rise in the U.S. and globally. Most of these accidents are cause by impaired or distracted driving. Existing systems that detect impaired driving use cameras that perform eye and head tracking and do not capture full-body movements that are indicative of dangerous driving. To address this problem, we present, distratto, a system that uses capacitive textile sensors embedded into car seats, headrests, and arm rests to capture whole body motion. The system also uses inertial and GPS sensors for determining vehicle speed and turns. Using a combination of these sensors and a tiered signal processing algorithm, we infer attributes that are indicative of impaired driving. We have developed a fully functional prototype of distratto that we evaluate in a real vehicle environment. We show that our system can detect impaired driving instances and driver movements with high accuracy.